Fog climatology analyses in coastal fog ecosystem at the Atacama Desert/Chile – spatio-temporal analysis of fog water characteristics and variability

2020 ◽  
Author(s):  
Juan Carlos Pastene ◽  
Alexander Siegmund ◽  
Camilo del Río ◽  
Pablo Osses
Keyword(s):  
Temporal Dynamics ◽  
Local Level ◽  
Global Radiation ◽  
Atacama Desert ◽  
Temporal Analysis ◽  
Local Network ◽  
Fog Water ◽  
Water Characteristics ◽  
Vertical Range ◽  
Spatio Temporal

<p>The coastal Chilean Atacama Desert comprise some of the driest areas of the world with anual mean precipitation partly less than 1 mm/year, like in the Tarapacá region. It is in these environments, where fog plays a relevant role for local ecosystems, like the so called <em>Tillandsia</em> Lomas. These fog ecosystems contain <em>Tillandsia landbeckii</em> as an endemic species, which covers a vertical range of about 800 to 1,250 m, related to fog availability. The study area “Oyarbide” (20°29’ S, 70°03’ W) is situated inland desert, over a range of 300 m elevation where the advective and orographic fog penetrate far enough to reach the east border of the site at around 1,200 m.</p> <p>On local level, the understanding of the fog climate characteristics and variability is still poor as well as knowledge about the driving parameters, the temporal dynamics and spatial gradients. For this reason, various parameters of fog climate are analysed and characterised on the basis of a local station network in order to determine the local fog climatology.</p> <p>From 2016, several high quality climatological stations (Thies Clima) were installed in “Oyarbide”, located in a transect from ca. 1,160 m to ca. 1,350 m in a distance between 10.3 km to 10.7 km from the coast. The local network of climate stations is generating a high temporal and spatial acquisition of climatological data of standard fog water (2 m), air temperature & humidity (2 m), surface temperature (5 cm), wind speed & direction (10 m & 2 m), air pressure, global radiation, leaf wetness and dew every 10 minutes until nowadays. Additionally, ten mini fog collectors (Mini FCs) were installed at the beginning 2019, covering a surface of ca. 3 km<sup>2</sup>, generating a monthly data of ground fog water collected (50 cm).</p> <p>First spatio-temporal analyses of different parameters of the local fog climate will be presented. The results of the study show a seasonal, monthly and daily variability, with altitudinal and vertical differences and oscillation. The results will serve as input for the understanding of the fog variability into hyperarid zones.</p>

scholarly journals Spatio-Temporal Patterns of the 2019-nCoV Epidemic at the County Level in Hubei Province, China

2020 ◽  
Vol 17 (7) ◽  
pp. 2563 ◽  
Author(s):  
Wentao Yang ◽  
Min Deng ◽  
Chaokui Li ◽  
Jincai Huang
Keyword(s):  
Temporal Dynamics ◽  
Spatial Interaction ◽  
Temporal Trends ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Hubei Province ◽  
Incidence Rates ◽  
County Level ◽  
Spatial Clusters ◽  
Spatio Temporal

Understanding the spatio-temporal characteristics or patterns of the 2019 novel coronavirus (2019-nCoV) epidemic is critical in effectively preventing and controlling this epidemic. However, no research analyzed the spatial dependency and temporal dynamics of 2019-nCoV. Consequently, this research aims to detect the spatio-temporal patterns of the 2019-nCoV epidemic using spatio-temporal analysis methods at the county level in Hubei province. The Mann–Kendall and Pettitt methods were used to identify the temporal trends and abrupt changes in the time series of daily new confirmed cases, respectively. The local Moran’s I index was applied to uncover the spatial patterns of the incidence rate, including spatial clusters and outliers. On the basis of the data from January 26 to February 11, 2020, we found that there were 11 areas with different types of temporal patterns of daily new confirmed cases. The pattern characterized by an increasing trend and abrupt change is mainly attributed to the improvement in the ability to diagnose the disease. Spatial clusters with high incidence rates during the period were concentrated in Wuhan Metropolitan Area due to the high intensity of spatial interaction of the population. Therefore, enhancing the ability to diagnose the disease and controlling the movement of the population can be confirmed as effective measures to prevent and control the regional outbreak of the epidemic.

scholarly journals Spatio-temporal dynamics of dengue in Brazil: seasonal travelling waves and determinants of regional synchrony

2018 ◽  
Author(s):  
Mikhail Churakov ◽  
Christian J. Villabona-Arenas ◽  
Moritz U.G. Kraemer ◽  
Henrik Salje ◽  
Simon Cauchemez
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Mosquito Control ◽  
Human Mobility ◽  
Travelling Waves ◽  
Seasonal Pattern ◽  
Temporal Analysis ◽  
Vector Ecology ◽  
Spatio Temporal ◽  
Dengue Epidemics

AbstractDengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years.Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterize the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period.We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence.This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.Author summaryIn this paper we studied the synchronization of dengue epidemics in Brazilian regions. We found that a typical dengue season in Brazil can be described as a wave travelling from the western part of the country towards the east, with the exception of the two most northern equatorial states that experienced inconsistent seasonality of dengue epidemics.We found that the spatial structure of dengue cases is driven by both climate and human mobility patterns. In particular, precipitation was the most important factor for the seasonality of dengue at finer spatial resolutions.Our findings increase our understanding of large scale dengue patterns and could be used to enhance national control programs against dengue and other arboviruses.

Intraannual fog variability and its relationship with spatio-temporal gradients in northern Chilean Atacama Desert

2020 ◽  
Author(s):  
Juan Carlos Pastene ◽  
Alexander Siegmund ◽  
Camilo del Río ◽  
Pablo Osses
Keyword(s):  
Atacama Desert ◽  
Arid Environment ◽  
Test Bed ◽  
Interconnected System ◽  
Fog Water ◽  
Stratocumulus Clouds ◽  
Coastal Fog ◽  
Spatial Differences ◽  
First Results ◽  
Spatio Temporal

<p>The coastal regions of the Atacama Desert comprise some of the driest areas of the world, with average annual precipitation mostly less than 1 mm per year. It is in these environments where the ocean-atmosphere interconnected system determines the spatio-temporal dynamic of an advective coastal fog, providing moisture out stratocumulus clouds from the Pacific Ocean to an hyper-arid environment and allowing the development of fog ecosystems and high biodiversity along the Atacama coast.<br />Studies about fog has been done in this region since the middle of the 20th century. However, there is a high quality knowledge gap about spatio-temporal fog dynamics on a local scale and its interaction of climate variables with topography. The study on fog climatology and its variability will be the basis for the analysis of complex biosphere-atmosphere interactions, in which the local ecosystems can act as bio-indicators for fog water availability and climate change.<br />The study area is situated in the Chilean coastal desert of Atacama in the Tarapacá region (20° S), where a transect of seven climatological stations located between 518 m and 1,354 m altitude, from the coast to 10.7 km inland, records a high temporal (hourly/10-minutes) atmospheric data. The climate stations measurement it is based on Standard Fog Collectors (SFC) and a broad set of atmospherical variables that allows determine the relationship between the spatio-temporal variability of the fog and its driving parameters.<br />First results show a significant local intraannual fog variability with marked spatial differences in fog water collected and its atmospherical parameters along longitudinal and altitudinal gradient. The fog dynamic could provide a test bed for analyzing, assess and modeling biosphere-atmospheric interactions and relating them to meso-climate regimes.</p>

scholarly journals Highlighting the Sustainability Implications of Urbanisation: A Comparative Analysis of Two Urban Areas in Ghana

Land ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 300 ◽  
Author(s):  
Kwasi Anarfi ◽  
Ross A. Hill ◽  
Chris Shiel
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Tenure ◽  
Urban Areas ◽  
Local Level ◽  
Population Data ◽  
Temporal Analysis ◽  
Resource Extraction ◽  
Market Forces ◽  
Spatio Temporal

Ghana is urbanising rapidly, and over half of the country’s population have lived in urban areas since 2010. Although research has proliferated to explore Ghana’s urbanisation, there is a dearth of research that holistically explores the wider sustainability implications of urbanisation, offers comparative perspectives in the context of large and smaller urban areas, and provides a perspective of local level urbanisation in the context of resource extraction (mining). This study comparatively assesses two urban areas in Ghana (Kumasi and Obuasi), by conducting a spatio-temporal analysis of land cover change through remote sensing and by analysing demographic change through a synthesis of published population data, in order to highlight the sustainability implications of urbanisation. The results show that urbanisation has been rapid, and has resulted in changes in land cover and demography in Kumasi and Obuasi. The sustainability implications of urbanisation are identified to include limited economic opportunities, socio-spatial segregation, and destruction of natural vegetation. The evidence in this study provides insights into urbanisation in Ghana, and suggests that the positive sustainability impacts of urbanisation may be eroded by how factors such as market forces and land tenure interact at the local level.

Spatio-Temporal Analysis of Freight Flows in Southern California

2021 ◽  
pp. 036119812110041
Author(s):  
Daniel Rivera-Royero ◽  
Miguel Jaller ◽  
Chang-Mo Kim
Keyword(s):  
Southern California ◽  
Temporal Dynamics ◽  
Capacity Utilization ◽  
Temporal Analysis ◽  
Heavy Duty ◽  
Additional Information ◽  
Weigh In Motion ◽  
Spatio Temporal ◽  
Truck Load ◽  
Vehicle Capacity

This paper analyses the spatio-temporal patterns of freight flows in Southern California using weigh-in-motion (WIM) data between 2003 and 2015. The study explores the spatial relationships between truck volumes, load ratios, and gross vehicle weights for different vehicle classes, through econometric and centrographic analyses during the study period. Overall, the results confirmed the existence of the logistics sprawl phenomenon, highlighted the effect of the 2008 to 2009 major recession in the concentration of freight facilities and flows, indicated that the changes in flow patterns vary for different vehicle classes, and found low vehicle capacity utilization for light- (WIM classes 5–7) and medium- (WIM classes 8–10) heavy-duty trucks, though recently improving. These results are consistent with the growth in residential deliveries owing to e-commerce, showing increased light-heavy-duty trucks flows concentrated closer to the consumption areas, and experiencing larger flow reductions compared to heavy vehicle flows as the distance from the area increases; and showing that medium-heavy-duty vehicles used in both full-truck-load, and less-than-truck-load vocations are prevalent throughout the study area, whereas there is a trade-off between light- and heavy-heavy duty trucks (WIM classes 11–13) at the proximity, and the outskirts of the consumption markets, respectively. Moreover, the study shows the usefulness of the WIM data in identifying spatial and temporal dynamics in freight demand, providing additional information for planning, maintenance, and rehabilitation of the infrastructure. More importantly, the results, coupled with other evidence from the literature, show how major disruptions such as the recession significantly affect truck traffic.

scholarly journals Spatio-temporal Evolution of Water-Energy-Food System Risk from the Provincial Perspective: A Case Study of China

2021 ◽  
Author(s):  
Tonghui Ding ◽  
Junfei Chen ◽  
Ming Li
Keyword(s):  
Economic Development ◽  
Lower Risk ◽  
Food System ◽  
Temporal Dynamics ◽  
Temporal Analysis ◽  
Development Level ◽  
Resource Endowment ◽  
System Risk ◽  
Risk Areas ◽  
Spatio Temporal

Abstract In this paper, the definition of Water-energy-food system risk (WEF-R) was firstly defined based on stability, coordination and sustainability. Set pair analysis and risk matrix were applied to assess the spatio-temporal dynamics of WEF-R in China from 2008 to 2017. The research results showed that stability subsystem had the greatest influence on the WEF-R, and sustainability subsystem was an important factor affecting the WEF-R. According to the spatial-temporal analysis, the risk levels of coordination and sustainable subsystems showed a gradual downward trend, while that of stability subsystem showed small fluctuations from 2008 to 2017. In terms of the WEF-R level, it presented a decreasing trend of small fluctuations. In addition, the higher-risk areas of stability subsystem and lower-risk areas of sustainability subsystem, which were mainly centralized in southeast coastal and central regions, were consistent with the areas of good economic development level and high level of urbanization. While the lower-risk areas of stability subsystem and higher-risk areas of sustainability subsystem, which were mainly centralized in the northwest regions, brought into correspondence with the areas of good resource endowment but lower levels of economic development. Therefore, the spatial differences of economic development level and resource endowment were the main factors affecting the spatial pattern of the WEF-R level in China. Therefore, policy makers should focus on WEF-R and implement measures to improve the sustainable development of WEF nexus.

scholarly journals Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017

2021 ◽  
Author(s):  
C&eacutedric St&eacutephane Bationo ◽  
Jean Gaudart ◽  
Dieng Sokhna ◽  
Mady Cissoko ◽  
Paul Taconet ◽  
...  
Keyword(s):  
Burkina Faso ◽  
Incidence Rate ◽  
Temporal Dynamics ◽  
Meteorological Data ◽  
Time Lag ◽  
Temporal Analysis ◽  
Health District ◽  
Control And Prevention ◽  
Spatio Temporal ◽  
Spatial Hotspots

Background: Malaria control and prevention programs are more efficient and cost-effective when they target hotspots or select the best periods of year to implement interventions. This study aimed to identify the spatial distribution of malaria hotspots at the village level in Diébougou health district, Burkina Faso, and to model the temporal dynamics of malaria cases as a function of meteorological conditions and of the distance between villages and health centers (HCs). Methods: Case data for 27 villages were collected in 13 HCs using continuous passive case detection. Meteorological data were obtained through remote sensing. Two synthetic meteorological indicators (SMIs) were created to summarize meteorological variables. Spatial hotspots were detected using the Kulldorf scanning method. A General Additive Model was used to determine the time lag between cases and SMIs and to evaluate the effect of SMIs and distance to HC on the temporal evolution of malaria cases. The multivariate model was fitted with data from the epidemic year to predict the number of cases in the following outbreak. Results: Overall, the incidence rate in the area was 429.13 cases per 1,000 person-year with important spatial and temporal heterogeneities. Four spatial hotspots, involving 7 of the 27 villages, were detected, for an incidence rate of 854.02 cases per 1,000 person-year. The hotspot with the highest risk (relative risk = 4.06) consisted of a single village, with an incidence rate of 1,750.75 cases per 1,000 person-years. The multivariate analysis found greater variability in incidence between HCs than between villages linked to the same HC. The epidemic year was characterized by a major peak during the second part of the rainy season and a secondary peak during the dry-hot season. The time lag that generated the better predictions of cases was 9 weeks for SMI1 (positively correlated with precipitation variables and associated with the first peak of cases) and 16 weeks for SMI2 (positively correlated with temperature variables and associated with the secondary peak of cases). Euclidian distance to HC was not found to be a predictor of malaria cases recorded in HC. The prediction followed the overall pattern of the time series of reported cases and predicted the onset of the following outbreak with a precision of less than 3 weeks. Conclusions: Our spatio-temporal analysis of malaria cases in Diebougou health district, Burkina Faso, provides a powerful prospective method for identifying and predicting high-risk areas and high-transmission periods that could be targeted in future malaria control and prevention campaigns. Keywords Geo-epidemiology, Spatial Clusters, temporal dynamics, nonlinear relationship, prediction.

scholarly journals Intelligent Drought Tracking for its Use in Machine Learning: Implementation and First Results

10.29007/klgg ◽  
2018 ◽  
Author(s):  
Vitali Diaz ◽  
Gerald A. Corzo Perez ◽  
Henny A.J. Van Lanen ◽  
Dimitri Solomatine
Keyword(s):  
Machine Learning ◽  
Temporal Dynamics ◽  
Temporal Analysis ◽  
Drought Monitoring ◽  
Grid Data ◽  
Drought Prediction ◽  
Documented Information ◽  
First Results ◽  
Spatio Temporal ◽  
Over Time

Due to the underlying characteristics of drought, monitoring of its spatio-temporal development is difficult. Last decades, drought monitoring have been increasingly developed, however, including its spatio-temporal dynamics is still a challenge. This study proposes a method to monitor drought by tracking its spatial extent. A methodology to build drought trajectories is introduced, which is put in the framework of machine learning (ML) for drought prediction. Steps for trajectories calculation are (1) spatial areas computation, (2) centroids localization, and (3) centroids linkage. The spatio- temporal analysis performed here follows the Contiguous Drought Area (CDA) analysis. The methodology is illustrated using grid data from the Standardized Precipitation Evaporation Index (SPEI) Global Drought Monitor over India (1901-2013), as an example. Results show regions where drought with considerable coverage tend to occur, and suggest possible concurrent routes. Tracks of six of the most severe reported droughts were analysed. In all of them, areas overlap considerably over time, which suggest that drought remains in the same region for a period of time. Years with the largest drought areas were 2000 and 2002, which coincide with documented information presented. Further research is under development to setup the ML model to predict the track of drought.

scholarly journals Análise Multitemporal dos Lençóis Maranhenses Entre 1984 a 2014 Utilizando Sensoriamento Remoto Orbital (Spatio-Temporal Analysis of Lençóis Maranhenses Between 1984 and 2014 Using Orbital Remote Sensing)

2016 ◽  
Vol 9 (1) ◽  
pp. 280
Author(s):  
Thiago Diniz Araujo ◽  
Eliana Lima da Fonseca
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Temporal Dynamics ◽  
Coastal Dunes ◽  
Temporal Analysis ◽  
Landsat 8 ◽  
Infrared Band ◽  
Trade Winds ◽  
Multi Temporal ◽  
Spatio Temporal

A análise multitemporal possibilita comparar uma mesma paisagem entre dois ou mais períodos, auxiliando no monitoramento das suas dinâmicas. O objetivo deste artigo foi analisar a dinâmica de caráter espaço-temporal do Parque Nacional dos Lençóis Maranhenses, mapeando as mudanças do sistema dunário a partir de imagens de satélite, no período de 1984 a 2014. Para esta análise foram utilizadas imagens de satélite adquiridas pelos sensores TM-Landsat 5 e OLI-Landsat 8. A borda limite do parque, na parte interior do continente, foi vetorizada para o ano inicial e final da análise, gerando mapas com o deslocamento das dunas no período de 31 anos o que permitiu identificar as áreas de avanço e retração do sistema dunário. A área total de avanço das dunas foi de 23,69 km² enquanto que a retração apresentou 14,95 km². Identificou-se expansão das dunas do litoral em direção ao interior do continente no sentido nordeste - sudoeste, seguindo a circulação dos ventos alísios. Foram selecionados quatro pontos de observações onde foram monitoradas as mudanças na cobertura do solo a partir da variação anual dos valores de reflectância da superfície na banda do infravermelho próximo, permitindo identificar o tipo de mudança quanto o tempo de ocorrência das mesmas.  A B S T R A C T The multi-temporal analysis allows comparing the same landscape between two or more time periods, assisting in the monitoring of its dynamics. The objective of this study were to analyze the spatio-temporal dynamics of the Parque Nacional dos Lençóis Maranhenses, mapping the changes in the dunes system using satellite imagery, from 1984 to 2014. For this analysis were used satellite images acquired by TM-Landsat 5 and OLI-Landsat 8 sensors. The park boundary, in the inner part of the continent, was vectored for the initial and final year of analysis, generating maps with the changes in the dunes locations in the 31 years period identified the forward areas and retraction and areas. The total area of advancement of dunes was 23.69 km² while the downturn area was 14.95 km². It was identified expansion of coastal dunes toward the interior of the continent towards northeast - southwest, following the movement of trade winds. Were selected four points of observations which were monitored changes in land cover from the annual change of the surface reflectance values in the near infrared band, allowing identify both the type of change and its time of occurrence.Keywords: remote sensing, environmental monitoring, migration of sediment. 

Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors

2001 ◽  
Author(s):  
Eckehard Schöll
Keyword(s):  
Temporal Dynamics ◽  
Spatio Temporal
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